• English
  • Deutsch
  • Log In
    Password Login
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. High-content screening data management for drug discovery in a small- to medium-size laboratory
 
  • Details
  • Full
Options
2012
Journal Article
Titel

High-content screening data management for drug discovery in a small- to medium-size laboratory

Titel Supplements
Results of a collaborative pilot study focused on user expectations as indicators of effectiveness
Abstract
High-content screening (HCS) technology provides a powerful vantage point to approach biological problems; it allows analysis of cell parameters, including changes in cell or protein movement, shape, or texture. As part of a collaborative pilot research project to improve bioscience research data integration, we identified HCS data management as an area ripe for advancement. A primary goal was to develop an integrated data management and analysis system suitable for small- to medium-size HCS programs that would improve research productivity and increase work satisfaction. A system was developed that uses Labmatrix, a Web-based research data management platform, to integrate and query data derived from a Cellomics STORE database. Focusing on user expectations, several barriers to HCS productivity were identified and reduced or eliminated. The impact of the project on HCS research productivity was tested through a series of 18 lab-requested integrated data queries, 7 of which were fully enabled, 7 partially enabled, and 4 enabled through data export to standalone data analysis tools. The results are limited to one laboratory, but this pilot suggests that through an "implementation research" approach, a network of small- to medium-size laboratories involved in HCS projects could achieve greater productivity and satisfaction in drug discovery research.
Author(s)
Berlinicke, C.A.
Ackermann, C.F.
Chen, S.H.
Schulze, C.
Shafranovich, Y.
Myneni, S.
Patel, V.L.
Wang, J.
Zack, D.J.
Lindvall, M.
Bova, G.
Zeitschrift
Journal of Laboratory Automation : JALA
Thumbnail Image
DOI
10.1177/2211068211431207
Language
English
google-scholar
CESE
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022